I'd like to use Google Cloud Functions to deploy a keras model saved in JSON (including weights in HDF5) with tensorflow as backend.
The deployment succeed when I don't specify tensorflow in requirements.txt. Although when testing the function in GCP, I get the error message specifying that tensorflow could not be found.
Error: function crashed. Details:
No module named 'tensorflow'
First, I find it quite strange that Google doesn't provide environments with tensorflow pre-installed.
But now if I specify tensorflow in requirements.txt, deployment fails with the error message
ERROR: (gcloud.beta.functions.deploy) OperationError:
code=3, message=Build failed: USER ERROR:
`pip_download_wheels` had stderr output:
Could not find a version that satisfies the
requirement tensorflow (from -r /dev/stdin (line 5))
(from versions: )
No matching distribution found for tensorflow (from -r
/dev/stdin (line 5))
Is there a way I can get tensorflow on Cloud Functions or Google deliberately blocks the install to get us to use ML Engine?